Estimating extreme quantiles under random truncation

Laurent Gardes () and Gilles Stupfler

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2015, vol. 24, issue 2, 207-227

Abstract: The goal of this paper is to provide estimators of the tail index and extreme quantiles of a heavy-tailed random variable when it is right truncated. The weak consistency and asymptotic normality of the estimators are established. The finite sample performance of our estimators is illustrated on a simulation study and we showcase our estimators on a real set of failure data. Copyright Sociedad de Estadística e Investigación Operativa 2015

Keywords: Asymptotic normality; Consistency; Extreme quantile; Heavy-tailed distribution; Tail index; 62G05; 62G20; 62G30; 62G32 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s11749-014-0403-5

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